Instructions to use BlackCatRoboticsAI/smolvla-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- LeRobot
How to use BlackCatRoboticsAI/smolvla-base with LeRobot:
# See https://github.com/huggingface/lerobot?tab=readme-ov-file#installation for more details git clone https://github.com/huggingface/lerobot.git cd lerobot pip install -e .[smolvla]
# Launch finetuning on your dataset python lerobot/scripts/train.py \ --policy.path=BlackCatRoboticsAI/smolvla-base \ --dataset.repo_id=lerobot/svla_so101_pickplace \ --batch_size=64 \ --steps=20000 \ --output_dir=outputs/train/my_smolvla \ --job_name=my_smolvla_training \ --policy.device=cuda \ --wandb.enable=true
# Run the policy using the record function python -m lerobot.record \ --robot.type=so101_follower \ --robot.port=/dev/ttyACM0 \ # <- Use your port --robot.id=my_blue_follower_arm \ # <- Use your robot id --robot.cameras="{ front: {type: opencv, index_or_path: 8, width: 640, height: 480, fps: 30}}" \ # <- Use your cameras --dataset.single_task="Grasp a lego block and put it in the bin." \ # <- Use the same task description you used in your dataset recording --dataset.repo_id=HF_USER/dataset_name \ # <- This will be the dataset name on HF Hub --dataset.episode_time_s=50 \ --dataset.num_episodes=10 \ --policy.path=BlackCatRoboticsAI/smolvla-base - Notebooks
- Google Colab
- Kaggle
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Download README.md from BlackCatRoboticsAI/smolvla-base: direct link, hf CLI and curl.
- Browser
- Download file 1.19 kB
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https://huggingface.co/BlackCatRoboticsAI/smolvla-base/resolve/main/README.md
- Command line
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hf download hf://BlackCatRoboticsAI/smolvla-base/README.md
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curl -L -o README.md https://huggingface.co/BlackCatRoboticsAI/smolvla-base/resolve/main/README.md
1.19 kB
| license: apache-2.0 | |
| task_categories: | |
| - robotics | |
| tags: | |
| - vla | |
| - vision-language-action | |
| - lerobot | |
| - manipulation | |
| - smolvla | |
| size_categories: | |
| - n<1K | |
| # SmolVLA Base | |
| **SmolVLA** — A compact Vision-Language-Action model from Hugging Face for robot manipulation. Takes images + language instructions, outputs robot actions. | |
| ## Model Details | |
| | Field | Value | | |
| |---|---| | |
| | **License** | Apache 2.0 (commercial use ✅) | | |
| | **Input** | Multi-view images (256×256) + language instruction + proprioception | | |
| | **Output** | Robot actions | | |
| | **Framework** | LeRobot / PyTorch | | |
| | **Format** | Safetensors | | |
| ## Quick Start | |
| ```python | |
| from huggingface_hub import snapshot_download | |
| from lerobot.policies.smolvla.modeling_smolvla import SmolVLA | |
| # Download model | |
| snapshot_download(repo_id="BlackCatRoboticsAI/smolvla-base", local_dir="./smolvla") | |
| # Load policy | |
| policy = SmolVLA.from_pretrained("./smolvla") | |
| ``` | |
| ## Use Cases | |
| - Pick-and-place manipulation | |
| - Object sorting | |
| - Assembly tasks | |
| - Language-driven control | |
| ## Citation | |
| ```bibtex | |
| @misc{lerobot2025smolvla, | |
| title={SmolVLA: Small Vision-Language-Action Model}, | |
| author={Hugging Face}, | |
| year={2025}, | |
| publisher={Hugging Face} | |
| } | |
| ``` | |